National Academies Press: OpenBook

Pavement Management Systems: Putting Data to Work (2017)

Chapter: Chapter Three - State of the Practice

« Previous: Chapter Two - Literature Review
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2017. Pavement Management Systems: Putting Data to Work. Washington, DC: The National Academies Press. doi: 10.17226/24682.
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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

28 Overview A web-based survey of practice was distributed to pavement management engineers in each of the 52 state transportation agencies (including Puerto Rico and the District of Columbia) and the 10 Canadian provincial MOTs to learn more about current practices in pavement management. A preliminary version of the questionnaire was tested by the Topic Panel prior to distribution. Forty state DOTs responded to the survey for a 80% success rate and Puerto Rico also responded to the survey, as shown in Figure 15. In addition, eight MOTs (80%) in the following Canadian provinces responded to the survey: • Alberta • Manitoba • New Brunswick • Newfoundland and Labrador • Northwest Territories • Ontario • Quebec • Saskatchewan. This chapter summarizes the findings from the survey of practices. A copy of the survey questions is provided as Appendix A (online only) and the responses received are presented in Appendix B. Survey COntent The survey questions were organized into the following three sections: • General Pavement Management Information—this section includes questions about respon- dents’ pavement management systems, the status of their highway inventory, the manner in which distress data are collected, and the types of information in their pavement management database. • Data Analysis and Performance Modeling—this section explores how performance mod- els are developed, the types of treatments included in the system, the analysis capabilities available in pavement management software, and the types of analyses that have been conducted. • Putting the Data to Work—the last group of questions addresses the degree to which funded improvements match the pavement management system recommendations and the factors influencing any significant differences. In addition, respondents were asked several questions about processes in place to update their data, the degree to which pavement management is integrated with other programs, the types of documentation in place, and the types of informa- tion shared with various stakeholder groups. The results of the survey are presented in the remainder of this chapter. In addition to the survey results, interviews were conducted with representatives from five state DOTs to explore nontradi- tional uses for their pavement management data. The results from the interviews are presented in chapter four. chapter three State Of the PraCtiCe

FIGURE 15 U.S. transportation agencies that responded to the survey.

30 General Pavement manaGement infOrmatiOn To learn more about the extent to which highway network attributes are incorporated into a pave- ment management database, respondents were asked to identify whether inventory and condition information exists for various components of the network. Separate questions were posed to U.S. and Canadian agencies to better reflect the terminology used in each country. For example, U.S. agencies were asked about the coverage on the NHS, a term not used in Canada. Responses to questions about coverage in the United States are presented in Figure 16 and the Canadian responses in Figure 17. As shown in Figure 16, all state DOTs that responded to the survey have inventory and condition infor- mation on their Interstate and non-Interstate NHS routes, which is consistent with federal reporting requirements for states providing data on these routes to the HPMS. Fewer than half of the state FIGURE 16 Number of state transportation agencies with inventory and condition information in their pavement management systems. FIGURE 17 Number of provincial MOTs with inventory and condition information in their pavement management systems (only seven provinces answered this question).

31 DOTs have inventory information for their frontage roads, entrance and exit ramps, and shoulders. Even fewer have condition information on that portion of their pavement network. The responses from the MOTs are similar to those reported by U.S. agencies because most of the agencies responding indicated that they have inventory and condition information on their provincial highways and the Trans-Canada Highway. Some agencies have inventory information on shoulders, frontage roads, entrance and exit ramps, and high-occupancy vehicle (HOV) lanes or bus lanes, but fewer than half of the agencies have condition information for that portion of their system. It is also possible that some agencies do not have HOV or bus lanes in their system. Agencies were then asked to select a statement from a list of options that best describes their pave- ment management software. Options included developing their system in house, using vendor-supplied software that has been modified by the agency, using proprietary software provided by a vendor, or using software in the public domain. Respondents were also given the option of selecting “other” and entering a singular response. The answers are shown in Figure 18. The use of vendor-supplied propri- etary software customized to meet the needs of the agency is by far the most common approach used in the United States. In Canada, three of eight agencies use customized proprietary software. Several agencies from the United States and Canada responded to the question by choosing “other” and providing the following information: • We use an Access database and Excel tools to work with the data and do pavement management activities. • We use vendor-supplied software that was customized for our use and then modified by in-house personnel (answer provided by two agencies). • Inventory only; no pavement management system in place. • No system currently in place. • Currently access—waiting to develop a permanent solution. • Pavement management components in multiple systems. • We use a vendor-provided program to optimize and other tools to view and analyze. • We use vendor-supplied condition data post-processing software, in-house software to collect construction data and warehouse all pavement data, and proprietary software for optimization and forecasting that was customized by the vendor. Agencies were also asked to provide information on the manner in which pavement distress data are collected on divided and nondivided highways. Agencies were allowed to choose more than one response if necessary. As shown in Figures 19 (divided) and 20 (nondivided), agencies are more likely to collect data in each direction on divided highways (44 of 49 responding agencies or 90%) than on nondivided highways (16 of 49 responding agencies or 33%). FIGURE 18 Type of pavement management software used.

32 Some of the responses to the “other” option included • On Interstates, data are collected in one lane in each direction. • In-house staff manually measure distress on samples of the downward imagery. • In addition to automated data, we perform a windshield survey that collects distress in all lanes in one direction (the primary direction). • Collect on all lanes on the NHS; otherwise in the right-most lane in each direction. • Collect on Interstates in both directions, state routes in one lane in one direction. • Rutting collected only. • If the nondivided highway has four or more lanes, collect data for only one lane in each direction. If the nondivided highway is less than four lanes, collect data in only one lane in one direction. • Two-lane routes are collected in only one direction. The last question in this section asked the respondent to select from a list each type of information that is included in their pavement management database. The results are provided in Figure 21 and FIGURE 19 Procedures used to collect distress data on divided highways. FIGURE 20 Procedures used to collect distress data on nondivided highways.

33 show that distress values are stored by most agencies along with composite and individual indices such as a rut index or a cracking index. Traffic data and treatment history and cost data are also com- mon in both the United States and Canada. The results also indicated that few pavement management databases contain information about routine maintenance activities, remaining service life (RSL), materials or construction information, or drainage. In addition, only three U.S. and three Canadian transportation agencies mentioned that detailed performance data from national or state pavement test sections are stored in their pavement management system. The 15 agencies that indicated that they store RSL in their pavement management database were asked how they define the term. The following six options were provided: • The time from the present (i.e., today) to when a pavement reaches an unacceptable condition. • The time until the next rehabilitation or reconstruction event. • The time until a condition index threshold limit is reached. • The time between applications of corrective pavement construction treatments. • The time until a remaining service interval is met. • Other. The responses received are presented in Figure 22. The most common definition is the time until a condition index threshold is reached; however, several states define it as the time until the next reha- bilitation or reconstruction event or an unacceptable condition is reached. The agency that selected “Other” noted that they define the RSL as an unacceptable condition level that has been established for each functional classification. Data analySiS anD PerfOrmanCe mODelinG The second set of questions explored the methods used for developing pavement deterioration mod- els and treatment rules, as well as the types of analyses that are conducted. FIGURE 21 Information contained in pavement management databases.

34 Performance modeling The first series of questions addressed pavement performance modeling. From a list of options, respondents were asked to select any of the approaches that they have used to predict pavement per- formance. The responses are provided in Figure 23, which shows that most agencies have developed agency-specific models and that many have developed models for pavement families with similar characteristics. Sixteen U.S. and two Canadian agencies reported that they predict the performance of individual distress and seven U.S. agencies develop individual models for each pavement section in their database. Only four U.S. and three Canadian agencies are using probabilistic models. In addition, four U.S. and one Canadian agency reported that their system does not predict pavement performance. FIGURE 22 Method of defining Remaining Service Life. FIGURE 23 Number of agencies using each approach to predict pavement performance.

35 Each of the 27 U.S. and six Canadian agencies that reported using customized models were asked a follow-up question intended to identify the factors that are used in developing the models. Respondents were allowed to choose as many responses as applicable. In addition, respondents were asked how frequently they update their performance models. The responses are provided in Figures 24 and 25. treatment Selection The next set of questions in this section of the survey focused on the type of treatment recom- mendations being used in the pavement management system. First, the survey asked respondents to identify whether their pavement management system recommends a treatment category (such as preservation or rehabilitation), a specific treatment type (such as chip seal or overlay), or both. A fourth option could be selected if treatment recommendations are not generated by the pavement management system. The responses to this question, which are presented in Figure 26, indicated that treatment categories are the most common; however, many pavement management systems FIGURE 24 Factors used to develop customized performance models. FIGURE 25 Performance model update frequency.

36 recommend specific treatments or both types of treatments. Five U.S. agencies and one Canadian transportation agency indicated that no treatment recommendations are generated in their pavement management system. The survey also asked respondents to identify the factors that are used in the pavement manage- ment system to identify a feasible pavement treatment. The responses, summarized in Figure 27, revealed that pavement condition, pavement type, traffic, pavement age, highway system, and the last treatment are the most commonly used to determine the appropriate treatment. Pavement layer and climate information are not used by many agencies. One reason why climate may not be used by some states is that the highways fall within a single climate region. Other responses indicated that several agencies either do not have a pavement management sys- tem in place or the system they use does not recommend treatments. One agency noted that on roads with curbs in place, treatment selection considers whether the road profile would be raised. Another indicated that studded tire wear is a factor in treatment selection. Finally, one agency indicated that considerations that are not included in the pavement management software are often noted during the field review of candidate projects. FIGURE 26 Types of treatment selection recommendations generated in a pavement management system. FIGURE 27 Factors used in selecting a feasible pavement treatment.

37 As noted in the literature review, over the last decade there has been an increased focus on incor- porating pavement preservation treatments into a pavement management system. The survey asked respondents to indicate whether their pavement management system includes preservation treat- ments such as chip seals and microsurfacing on asphalt-surfaced pavements and diamond grinding or dowel-bar retrofit on concrete pavements. As shown in Figure 28, the responses indicated that most agencies consider these types of treatments in their pavement management analysis. analysis Capabilities The final series of questions in this section explored the types of analyses that can be done with their pavement management software, whether or not it is actually used for that purpose. For each type of analysis selected, a follow-up question was asked to determine whether the agency has actually used the analysis. The difference in responses can be viewed by comparing Figures 29 and 30. The graphs show that whereas some pavement management features are being used extensively (such as forecasting conditions under different funding scenarios and estimating funding needed to achieve performance targets), there are many features that are not commonly being used. The least common applications include allocating funding to regions, preparing HPMS submittals, FIGURE 28 Number of agencies that include pavement preservation treatments in their pavement management system. FIGURE 29 Number of pavement management systems with these capabilities.

38 verifying performance models using field data, and developing contractor performance specifica- tions and/or measures to monitor warranty projects. Agencies that selected the “Other” option noted that some of these analyses are performed outside of a pavement management system using other tools. Another question asked whether the cost estimates in the pavement management system include the cost of nonpavement-related activities, such as striping or guardrail repairs. As shown in Figure 31, most agencies in the United States include these costs in their treatment costs, but this is much less common in Canada. PuttinG the Data tO wOrk The last set of questions pertains to how the pavement management data are being used. The first question focused on the extent to which projects that are included in a transportation improvement plan match the recommendations generated by the pavement management system. Agencies were asked to estimate the extent to which projects matched at least 70% of the time, between 40% and 70% of the time, or less than 40% of the time. An “I don’t know” option was also provided. The FIGURE 30 Number of agencies using each type of analysis. FIGURE 31 Number of agencies that include the cost of nonpavement-related activities in their treatment costs.

39 responses are shown in Figure 32. Only three U.S. and one Canadian agency reported that their improvement projects are substantially different than what is recommended in their pavement man- agement system; however, the survey responses do not indicate how a match is defined. Ideally, a match to the pavement management system would reflect the same level of repair, treatment timing, and project limits suggested in the analysis. In reality, agencies may allow for some flexibility in defining a match if, for example, a project will be constructed within 1 to 2 years of the recommenda- tion provided by the pavement management system and the pavement conditions have not changed substantially. The four agencies that reported a match less than 40% of the time were then given a follow-up question asking them to identify the factors that influenced the lack of a match. The results are pre- sented in Figure 33. The responses indicated that political influence, local conditions, the lack of sufficient funds, and district independence are all factors that influenced the final selection of proj- ects. Other responses included resource constraints in developing plans for small, but economical, projects and the agency’s lack of confidence in one of the treatment triggers. The same four agencies were asked to identify the factor that has the greatest influence on the lack of a match if they selected two or more of the options from the previous list. There were only three agencies that fit these criteria and the responses are shown in Figure 34. FIGURE 32 Estimated match between pavement management recommendations and funded projects. FIGURE 33 Number of agencies indicating each factor influenced the lack of a strong match between their improvement program and their pavement management recommendations.

40 Pavement management Processes, integration, and Documentation Three survey questions were included to learn more about processes to keep the pavement manage- ment system current, the amount of integration with other programs, and the types of documentation that exist. The first of these three questions asked respondents to select each of the processes in place to update the agency’s pavement management system. The responses are provided in Figure 35, which shows that most agencies have processes in place to update work history information, verify the quality of data, and update pavement surface type based on work activities. Less common is a process to update the database with actual project costs. The integration question asked respondents to identify from a list each of the computer systems that is integrated with the pavement manage- ment software. As shown in Figure 36, the two most commonly integrated systems are the agency’s GIS and its centralized roadway database. Fourteen agencies (12 in the United States and two in Canada) reported that their pavement management system is not integrated with any other system. Several agencies indicated that their pavement management system is integrated with their agency’s maintenance management system, asset management system, and/or bridge management system. Respondents were also asked to identify the type of documentation that was in place to institu- tionalize parts of the pavement management process, responses are presented in Figure 37. Condition survey procedures are most commonly documented, but a significant number of agencies have also documented their treatment rules and performance model equations. Agencies that selected “Other” noted that they are in the process of developing a manual (two agencies), that their processes are well established but not documented, or that they have a manual only for their visual rating procedures. FIGURE 34 Fact or having the greatest influence on the lack of match between pavement management and the construction program. FIGURE 35 The number of agencies with each process in place to support pavement management.

41 Pavement management information Provided to various Stakeholders As discussed in the literature review, pavement management information is presented in a number of different ways. To learn more about the types of pavement management information that are provided to various stakeholder groups, a list of the different types of information was presented and respondents were asked to identify each stakeholder group that receives that type of informa- tion. The responses are presented separately for the U.S. and Canadian agencies (Figures 38 and 39, respectively). The reporting of present pavement conditions is most common in both the United States and Canada; however, Canadian provinces are reporting forecasted conditions more than the state DOTs. The most common information provided to elected officials is current and forecasted conditions and FIGURE 36 The number of agencies with a pavement management system that is integrated with other agency systems. FIGURE 37 Number of agencies with documentation in place.

42 FIGURE 38 Number of U.S. agencies providing information to various stakeholder groups. FIGURE 39 Number of Canadian agencies providing information to various stakeholder groups.

43 pavement needs. Agency decision makers receive that information, but also are provided information about candidate projects and how the funding will be used. enhancements The final series of questions focus on desired enhancements to the pavement management system. First, a list of different types of enhancements was developed that included capabilities such as col- lecting network-level surface property and friction data, changing from a sampling approach for condition surveys, and updating pavement management software. For each item in the list, respond- ers were asked to identify whether that enhancement had already been done or whether it would be done within the next 2 years. The responses for the U.S. agencies are shown in Figure 40 and for Canadian agencies in Figure 41. In the United States, transportation agencies reported that they have developed, or will be developing, improvements in their quality management processes and in the updating of their pavement management software. It appears that many states have changed from manual to automated surveys and have moved to continuous surveys rather than the use of sampling. There appears to be a good deal of interest in using pavement management to optimize resource allocations and analyze investment needs across asset types. In Canada, the same types of changes are being made to pavement condition surveys; however, there are also a significant number of agencies that noted that they intend to increase the frequency of their surveys. The largest number of responses for a future enhancement relates to collecting pave- ment structural information at the network level. The final two survey questions required text responses. One asked responders to list any data they would like to, but do not currently, collect. The responses indicated that agencies would prefer to have the following information: • Structural data, such as deflection testing (six agencies). One respondent stated that the data would be used in the MEPDG software. Two agencies expressed interest in collecting these data at traffic speeds. FIGURE 40 Number of U.S. agencies that have made, or plan to make, certain enhancements.

44 • Pavement layer data, mix design properties, and/or material information (six agencies). Three of the agencies specifically indicated they would like network-level ground penetrating radar (GPR) data. One agency noted that it would like to improve the link between its pavement material data with the pavement management system. • Automated network-level surveys for roughness and cracking (three agencies). • Surface texture and skid data (three agencies). • Light Detection and Ranging (LiDAR) surveys (two agencies). One agency indicated the infor- mation would be used to evaluate the cross slope across all lanes for the network. • Specific distress information (two agencies). One agency expressed interest in collecting pot- hole information and the other listed raveling. • One agency expressed interest in building a rumble strip inventory. The responses indicate that pavement structural information is important as is the ability to improve the link between pavement management data and other types of pavement construction and material data. The last question asked whether the pavement management system had been used in an innova- tive manner. The agencies that responded affirmatively were interviewed and their innovations are included in chapter four. CrOSS analySiS Of the Data To further investigate trends in the survey results, an analysis was conducted to determine whether relationships could be established between the availability of certain types of data, the processes used to develop models, and the use of the pavement management software to conduct certain types of analyses. Only a limited number of these correlations were investigated; however, the findings present some interesting relationships. FIGURE 41 Number of Canadian agencies that have made, or plan to make, certain enhancements.

45 In response to the question regarding the processes that are in place to support pavement manage- ment (see Figure 35), 38 agencies reported that they have a process in place to verify the quality of their data. Within the agencies that have these processes in place: • Twenty-six (68%) update their performance models on at least a 3-year cycle. Overall, 30 agen- cies indicated that they update their performance models on a 3-year or less cycle. • Eleven (29%) reported that performance models are verified using field data. These findings tend to support the theory that agencies that have confidence in their pavement performance data update their performance models regularly. Approximately 30% of these agencies verify the updated models using field data. Figures 29 and 30 presented the results from questions exploring the availability of certain capa- bilities in the pavement management software and the use of these capabilities by agency personnel. Thirty-four agencies indicated that their pavement management software was capable of evaluating the cost-effectiveness of different treatments. Only 23 (68%) noted that they had used their pave- ment management system to conduct this type of analysis. Exploring other responses provided by the agencies, the strongest correlations in other data observations are presented in Table 1. The findings indicated that the agencies that have conducted a cost-effective analysis using their pavement management system are not necessarily the same agencies that are performing these other functions regularly. It also appears that these agencies tend to use RSL more than other agencies, since overall only 16 of the 49 that answered the question (33%) noted that they include RSL in their system. The final comparison investigated the responses of the nine agencies that listed some form of structural condition assessment (e.g., Falling Weight Deflectometer or GPR) as additional data they wished they collected. The analysis revealed that four of these agencies (44%) develop performance models based on structural condition, indicating that improved structural information would support these efforts. Other Properties Identified Number of Agencies Whose Software Has the Ability to Evaluate Treatment Cost-Effectiveness Analysis That Also Perform the Properties Listed (Max 34) Number of Agencies That Have Used Their Software to Evaluate Treatment Cost-Effectiveness Analysis That Also Perform the Properties Listed (Max 23) Include RSL in Their Pavement Management System 11 (32%) 10 (43%) Verify Their Pavement Performance Models 20 (59%) 5 (22%) Update Their Pavement Performance Models Regularly (at least every 3 years) 23 (68%) 8 (35%) TABLE 1 TRENDS IN EVALUATING THE COST-EFFECTIVENESS OF DIFFERENT TREATMENTS

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TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 501: Pavement Management Systems: Putting Data to Work documents current pavement management practices in state and provincial transportation agencies. The report focuses on the use of pavement management analysis results for resource allocation, determining treatment cost-effectiveness, program development, and communication with stakeholders.

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